To address the limitations of the RRT* algorithm in effectively optimizing non-convex and asymmetric path costs for unmanned sailboats in fixed wind fields, this study proposes an improved RRT*-based path planning algorithm with the objective of minimizing sailing time. Firstly, an adaptive sampling strategy based on the Beta distribution is designed to establish a directional-biased non-uniform sampling mechanism, enabling targeted sampling in goal-oriented regions. Subsequently, a dynamic step-size adjustment strategy incorporating real-time vessel speed feedback is introduced to enhance search efficiency. Next, a polynomial interpolation model is constructed to simulate sailboat speed under varying wind angles, establishing a quantitative relationship between sailing speed and wind angle to achieve precise sailing time calculation. Finally, the bisection method is employed to further optimize the sailing path for reduced voyage duration, with Bézier curves utilized for path smoothing. Simulations conducted in the Matlab R2024a environment demonstrate that, across diverse fixed-wind scenarios, the proposed improved RRT* algorithm significantly reduces sailing time compared to both standard RRT* and Q-RRT* algorithms. The enhanced algorithm provides reliable path planning support for autonomous navigation of unmanned sailboats in wind field environments.

Aiming at the problem that traditional ship machinery fault diagnosis methods usually only focus on a single fault scenario and lack the ability to diagnose concurrent faults across domains, an intelligent fault diagnosis framework based on fully connected multilabel domain adaptive neural network (FMANN) was proposed. Firstly, the joint domain adaptation method was introduced to achieve the fault feature transfer under different working conditions, effectively solving the problem of small sample fault diagnosis under target working conditions. Secondly, by introducing a multilabel classification method to capture the complex relationships among different faults, the migration diagnosis of concurrent faults has been achieved. Finally, the performance of several common domain adaptation methods under this framework was compared and analyzed, and the effectiveness and robustness of the proposed framework were verified by using the degradation dataset of a certain ship gas turbine propulsion system.

This paper studied the liquefied natural gas maritime inventory routing problem (LNG-MIRP) with the mode of shipping logistics company managed inventory. Based on the relationship between LNG boil off rate, temperature difference inside and outside the cabin, and cargo volume, the LNG boil off functions for each voyage and port loading/unloading process were established. An LNGMIRP nonlinear stochastic programming model was constructed by considering changes of LNG boil off rate with the objective of minimizing the total cost of maritime logistics companies. Then, the model was transformed into a mixed integer linear programming model by employing the two model transformation methods of chance constraint and piecewise linear secant approximation. Taking the LNG project from Yamal to China as an example, the proposed model and its algorithm were validated and analyzed. The results show that considering changes of boil off rate within LNGMIRP can significantly reduce ship fuel costs and LNG boil off losses, thereby saving the total logistics costs. Sensitivity analysis indicates that an increase in LNG prices will lead to an increase in total logistics costs. The research conclusions can provide useful references for LNGMIRP decisionmaking of maritime logistics companies.

With the rapid advancement of autonomous vessel technology, future port channels will witness mixed navigation involving both autonomous and conventional ships. A key challenge lies in ensuring navigational safety while enabling effective coordination between autonomous and traditional vessels during port entry and exit, thereby maximizing channel throughput. This paper proposes a formation strategy for autonomous vessels tailored to mixed traffic scenarios in ports and develops a robust macroscopic modeling framework to assess the impact of such strategies on channel capacity. Two formation strategies are introduced: cooperative formation and random formation. A comparative analysis is conducted under varying traffic demands and autonomous ship penetration rates. Experimental results show that at medium penetration rates, the impact of autonomous formations on channel capacity is minimal; however, at high penetration rates, the impact becomes significant. The cooperative formation strategy outperforms the random one in terms of capacity enhancement. The proposed formation strategies for autonomous ships can effectively enhance channel capacity in mixed navigation scenarios, providing theoretical support and technical guidance for future optimization of port and channel traffic management.

In order to meet the development needs of lightweight, high power density and high reliability of marine power system, ZL109 aluminum alloy has been widely used in piston manufacturing due to its low density, high strength ratio, light weight and excellent mechanical properties under the special working conditions of cylinder liner-piston friction pair in marine low speed diesel engine. The working environment of the cylinder liner-piston friction pair is often under the condition of poor oil lubrication, resulting in partial semi-dry friction or even dry friction. To enhance the wear resistance of the ZL109 aluminum alloy surface, many scholars have studied the surface strengthening treatment technology of ZL109 aluminum alloy. However, traditional surface treatment technologies still have some deficiencies in terms of cost and coating performance. Micro-arc oxidation, also known as liquid phase plasma electrolytic oxidation, is an advanced metal surface treatment technology. It generates micro-arc discharge at the interface between the metal and the electrolyte through precisely controlled pulsed current, thereby promoting the formation of a dense and highly adherent oxide film on the metal surface. Micro-arc oxidation technology has the advantages of low cost, environmental friendliness, no need for strict surface pretreatment, and the ability to control the surface morphology of the ceramic layer through process parameters. Therefore, it is easy to combine with other technologies to prepare functional coatings. The novel mechanism is established through surface-modified micro-arc oxidation (MAO) coatings and a kind of lubricant additive (MoS₂). The surface-modified micro-arc oxidation is accomplished by aminating the surface of MAO coatings with 3-aminopropyl triethoxysilane. To analyze the influence of micromorphology of MAO coatings on the novel anti-friction and anti-wear mechanism, the coatings prepared by different forward duty cycles were systematically studied in terms of reaction process, micromorphology, thickness, surface roughness and chemical composition. Friction and wear tests were carried out to characterize the tribological property of the MAO coatings. The microstructure, thickness, porosity and average pore size of the ceramic layer were analyzed by scanning electron microscopy, Image J software, optical profilometer and X-ray diffractometer. Then, amino functional groups were introduced on the surface of the ceramic layer by amination treatment. The surface modified ceramic layer was detected by infrared spectrometer, and the amino functional group was successfully grafted on the surface of the ceramic layer. Combined with the lubricating oil containing MoS₂, a stable chemical adsorption film of MoS₂ at the friction interface was formed at the friction and wear scratches. The results show that a chemical adsorption film of MoS₂ was successfully established on the surface of worn surface by surface amination, the action of frictional physical and chemical reactions, and the micro-contact formed by the porous promontories fabricated by MAO. Furthermore, the coefficient of friction was reduced by around 50 percent compared with the level of the MAO coating without amination and ZL109 substrate, and the wear amount of the coating prepared by duty cycle 70% is near 0.3 mg.

This paper proposes a novel rudder device based on the Magnus effect. By using the Computational Fluid Dynamics (CFD) simulation method, the lift/drag characteristics of the Magnus rudder were analyzed. Firstly, the geometric model of the Magnus rudder was created through SolidWorks software. Secondly, steady-state fluid analysis of the Magnus rudder was conducted using ANSYS-Fluent, focusing on the changes in lift/drag under different rotational speeds and the influence of the rotational speed ratio on performance. Thirdly, a comparative study on the lift/drag characteristics between the traditional ship rudder and the Magnus rudder was carried out. The simulation results show that the Magnus rudder generates significantly greater lift during operation compared to the traditional rudder, and its drag is relatively smaller, demonstrating superior lift-to-drag ratio characteristics. Finally, a PID rotational speed control system for the Magnus rudder driven by a hydraulic motor was established on the Matlab-Simulink platform, providing an effective control solution for the practical application of the Magnus rudder.

The IHO S-98 standard defines the interoperability between electronic navigational charts (ENCs) and multi-source hydrographic data as a future application trend. This study aims to explore intelligent techniques for generating dynamic depth contours by integrating ENC products with real-time water level data. In scenarios where S-102 bathymetric surface data are incomplete, the sparse depth data contained in ENC products are insufficient to directly support high-reliability dynamic depth computations. To address this limitation, we propose a deep learning-based super-resolution solution. Specifically, an improved TSE-EDSR model is employed to reconstruct a high-fidelity digital elevation model (DEM) of the seabed from sparse chart soundings. By further integrating real-time water level data, dynamic depth contours are generated. Experimental results demonstrate that the proposed method produces DEMs and dynamic depth contours with significantly higher accuracy and morphological authenticity compared to traditional interpolation approaches. This work provides technical support for S-98 interoperability applications and holds substantial theoretical and practical value for advancing the development and application of next-generation electronic navigational charts.

To effectively estimate the parameters of ship maneuvering motion models, this paper proposes a nonlinear identification method based on the threeparameter simplex algorithm (SA). A precision indicator function is constructed based on experimental data to establish a discrepancy criterion between model outputs and experimental data. It performs geometric operations such as reflection, expansion, and contraction in a threedimensional parameter space to achieve iterative optimization of parameters. The algorithm undergoes continuous iteration until it meets the convergence criterion, ultimately obtaining the globally optimal parameter combination that minimizes the indicator function. The proposed SA algorithm is applied to identify the parameters of the Norrbin model for the Mariner ship, and support vector machine (SVM) and extended Kalman filter (EKF) algorithms are used as comparison methods to systematically analyze identification performance. It can be seen from the calculation of the relative errors of the parameters obtained by each method that the identification accuracy of the SA algorithm is significantly superior to that of the other two methods: the relative error of its parameters is 0.022% for all cases, with the maximum error not exceeding 0.041%; the relative error of the EKF algorithm ranges from 8.150% to 32.068%, while the relative error of the SVM algorithm is 11.2% for all parameters, and the error of some parameters even exceeds 20%. The results show that the model identified by the SA algorithm is more consistent with the actual maneuvering performance of the ship. Furthermore, in terms of algorithm structure, the SA method is more concise than the SVM and EKF algorithms, requires fewer preset parameters, and therefore exhibits better practicality and engineering applicability.

Oscillating flow can exert forces on structures immersed in it, resulting in flow-induced vibration and other problems. The vortex-induced vibration (VIV) of a circular cylinder in a non-zero mean oscillatory flow at different frequencies is simulated, and the characteristics of the vortex-excitation vibration response are investigated. Numerical simulations were conducted on the superposition of uniform flow and high- and low-frequency oscillating flows. The displacement response, lift-drag coefficient, and vortex field morphology of the cylinder were then compared under different flow conditions. The results show that under high-frequency oscillating flow conditions, the vibration response of the cylinder is similar to that under uniform flow conditions, with a constant displacement amplitude that is in phase with the lift coefficient, and a vortex shedding frequency close to the structural frequency. In contrast, low-frequency flow induces periodic "growth-decay" behavior in the displacement time history, significantly reducing the root-mean-square and peak displacement values compared to uniform flow. It is found that the lift coefficient exhibits an anti-phase relationship with displacement during certain intervals, effectively suppressing structural vibration. Additionally, the vortex shedding structure in the wake is affected by the oscillating incoming flow, resulting in a different flow pattern than that of uniform flow.

To address the problem of unbalanced power allocation and unstable bus voltage in shipboard distributed power battery system under weak grid support conditions, a hierarchical cooperative stabilization control method is proposed. This method is based on the layered control idea, which divides the controller of the power battery converter into the main control layer, observation layer and cooperative control layer. In the main control layer, the droop control link is removed, and a droop-free control framework based on a distributed communication mechanism is constructed to solve the inherent contradiction between power equalization and voltage regulation in traditional droop control. In the observation layer, a dynamic diffusion algorithm is utilized to iteratively calculate the average state variables at local power battery converters, which drives the distributed averaging calculation process to converge smoothly and solves the communication data congestion problem between neighboring power battery converters. In the cooperative control layer, a multi-objective cooperative stabilization controller is designed to achieve composite dynamic equalization of State-of-Charge and State-of-Health, load power allocation by capacitance, and stable regulation of average bus voltage. The experimental results show that the proposed method can extend the service life of distributed power battery system by 20%, and the average bus voltage transient deviation is controlled within 0.6%. This method can provide a reference to the application of the operation control for the power battery system in new energy ships.

In response to changes in the shipping market and the demands of low-carbon transformation, shipping companies need to regularly optimize fleet deployment decisions for their routes. To enhance the objective of decisionmaking efficiency of shipping companies, a joint optimization model for fleet deployment and speed in liner shipping networks was formulated, and multiple factors such as ship type selection, cargo allocation across routes, and various green shipping measures were considered. Considering the inherent sequential decisionmaking characteristics of this model, a twostage interactive algorithm incorporating linear transformation and cascading increment strategies was proposed for efficient solution, and the accuracy and efficiency of this algorithm were validated through algorithm comparison and analysis. Compared to the algorithm that enumerates ship types, this algorithm improves solution efficiency by approximately 99% while achieving equivalent optimization results. Finally, taking the TransPacific shipping network as a case study to investigate optimal fleet deployment strategies. Results show that utilizing ships with larger container capacity while moderately increasing sailing speeds can significantly enhance operational profitability of carriers. The research findings can provide decision support for shipping companies to flexibly respond to market changes and efficiently formulate business strategies.

A three-dimensional numerical simulation was carried out on a diffuser cascade with a cavity structure, and improvements were made to the cavity by adding a rotor inside and varying its position and size. Comparative analysis was conducted on the flow field structures and performance parameters of different improved schemes. The results show that the modified cavity structures can reduce the overall total pressure loss coefficient and entropy generation loss coefficient of the cascade. When the rotor is placed near the leakage outlet cavity, the total pressure loss coefficient decreases by 16.4% compared to the original configuration, although the reduction in entropy generation loss coefficient is not significant. When the rotor is located near the leakage inlet cavity, the total pressure loss coefficient decreases by 12.0%, and the overall entropy generation loss is reduced, with the entropy generation loss coefficient decreasing by 13.0% compared to the prototype. After the leakage flow gains energy from the rotor within the cavity, its circumferential velocity increases. Upon mixing with the mainstream, the strengthened resistance to crosswise secondary flows improves the flow in the cascade passage. The migration of low-energy fluid along the spanwise direction near the endwall is reduced, the spanwise extent of corner separation is diminished, and the aerodynamic performance of the stator blades is enhanced.

Against the backdrop of advancing national low-altitude economy strategies, this research examines the factors and mechanisms influencing user acceptance of two differentiated low-altitude air travel services: the fixed-route shuttle (public service type) and 'Feidi' (market-oriented service type). By refining the integrated Technology Acceptance Model–Theory of Planned Behavior (TAM–TPB) framework, a multidimensional "technology-institution-cognition" analytical framework was constructed and empirically validated using a dual-scenario structural equation modeling approach based on questionnaire survey data. The findings reveal that fixed-route shuttle services exhibit a technology-function-dominated decision-making logic, where technology trust not only directly drives usage intention but also indirectly enhances acceptance by improving perceived usefulness and reducing risk perception. In contrast, 'Feidi' services follow an experience-driven decision-making pathway, where technology trust indirectly influences usage intention through attitude, with user decisions relying more heavily on perceived behavioral control and subjective experience. Drawing from the underlying user decision mechanisms, differentiated strategic guidance is provided for manufacturers' technology development priorities, operators' user experience optimization, and regulatory authorities' institutional design, thereby offering theoretical foundation and operational direction for promoting the industrial application of low-altitude air travel services.

Ship trajectory prediction is a core technology for intelligent shipping, yet existing models suffer from high computational costs, inadequate modeling of global spatio-temporal dependencies, and lack of privacy protection when processing long-sequence data. To address these challenges, this paper proposes a ship trajectory prediction and privacy-preserving scheme based on Mamba-Transformer fusion. The scheme innovatively designs a dual-path parallel architecture in the trajectory prediction module, efficiently capturing long-range temporal dependencies through the linear scaling capability of the Mamba branch while leveraging the powerful global modeling capability of the Transformer branch to extract macroscopic trajectory patterns. Deep fusion is achieved through a hierarchical multi-head attention module designed in this work, thereby effectively capturing both local navigation details and global trajectory patterns simultaneously. Furthermore, recognizing that real-time trajectory prediction poses higher privacy leakage risks compared to delayed publication, the proposed scheme introduces a differential privacy mechanism at the model output layer, with a time-decay-based privacy budget allocation strategy that significantly enhances the utility of published trajectories under privacy protection. Experimental results on the Danish maritime dataset demonstrate that the proposed scheme achieves substantial improvements in ship trajectory prediction accuracy over existing methods while providing rigorous privacy guarantees for high-precision predictions through a flexible differential privacy mechanism.

In response to the industry pain point of high cost of ocean freight empty container repositioning, an innovative combination of shipping company cooperation mechanism and free detention time strategy is proposed. Taking into account four channels for obtaining empty containers, namely container repositioning, storage, rental, and exchange, a nonlinear programming model is constructed with the goal of minimizing the total cost of empty container repositioning. By designing an approximate dynamic programming algorithm based on  greedy strategy, the multi-period decision-making and nonlinear coupling problems that traditional methods are difficult to handle have been solved, and the optimal decision for the length of free container period in different scenarios has been provided. Research has found that setting a reasonable free container detention period can reduce container rental costs and optimize container usage costs under cooperation with shipping companies. Sensitivity analysis shows that when the supply of empty containers exceeds the demand, the total cost of empty container management for shipping companies will reach its optimal level. For every 33% increase in inland container volume or 1 day extension in transportation time, the free detention period needs to be shortened by 1-2 days to achieve cost optimization. This collaborative decision-making framework helps improve the efficiency of empty container resource turnover in shipping companies and provides a basis for determining the length of free detention period for shipping companies. 

The safe and stable operation of marine engines is critical to national security and maritime traffic safety. While numerous deep learning methods have been extensively studied for intelligent fault detection, the complex operating conditions of marine engines—such as non-stationary states including variable loads—often lead to prevalent domain shift problems in practical fault diagnosis tasks. This significantly degrades the performance of conventional deep learning approaches. Using a specific marine engine as a case study, we constructed partial-set fault diagnosis scenarios under varying operating conditions. To address the challenge of missing fault labels in the target operating condition, we propose a knowledge transfer approach from source to target operating conditions. A novel Multi-scale and Multi-view Domain Adversarial Network (MMDAN) is designed and experimentally validated using marine engine data. Experimental results demonstrate that the proposed method achieves an average diagnostic accuracy of 96.58%. Furthermore, in partial-set transfer tasks across different operating conditions, MMDAN exhibits superior diagnostic performance compared to other state-of-the-art learning models.

In modern industrial systems, mechanical vibration monitoring technology plays a crucial role in ensuring equipment safety and preventing failures. This study proposes a highly sensitive liquid metal-based vibration sensor based on a triboelectric nanogenerator (TENG) for real-time vibration monitoring of marine mechanical equipment. The sensor consists of conductive fabric, Fluorinated Ethylene Propylene (FEP) film, and liquid metal, utilizing the triboelectric effect to convert mechanical vibrations into electrical signals. Experimental verification shows that this sensor exhibits excellent linear voltage response (R 2=0.995) within the dynamic acceleration range of 5 to 50 m/s², with a sensitivity of 0.218 V·m⁻¹·s². It also has good durability, and the signal attenuation can be ignored after 21,600 acceleration fatigue tests. It was ultimately successfully applied to the vibration monitoring of ship air compressors. Compared to traditional piezoelectric and electromagnetic sensors, this technology offers advantages such as high sensitivity, electromagnetic interference resistance, and flexibility to adapt to harsh environments, providing a novel solution for condition monitoring of equipment in demanding operational scenarios such as marine applications.

Focusing on the impact of lubricating oil vapor on low-speed two-stroke diesel engine performance, this study employed a combined approach of numerical simulation and bench testing. By developing an engine model and a lubricating oil vapor model, and coupling the combustion mechanism with physical parameters of diesel fuel and lubricating oil components, we revealed how the introduction of lubricating oil vapor triggers reorganization of the radical network, thereby influencing combustion characteristics and emission behaviors. The results showed that the introduction of lubricant vapor led to an increase in H/HOOH (hydrogen and hydroperoxyl radicals) and a decrease in O/OH (oxygen and hydroxyl radicals), which prolonged the stagnant combustion period of diesel fuel (CA0-10 increased by 1.1°CA) and accelerated the process of main combustion period (CA10-90 decreased by 4.84°CA). The increase of H radicals promoted the hydrogenation of soot precursors and inhibited soot nucleation and surface growth, resulting in an 18% decrease in peak soot emissions. In contrast, the reduction of OH radicals weakened the process of CO oxidation to CO₂ deep conversion, resulting in a 6.8% decrease in peak CO emissions. The H/O radicals triggered the recombination of hydrocarbons through hydrocarbon cleavage, resulting in a 5.8% increase in peak unburned hydrocarbons (HC). The H/O/HO₂ radical cycle accelerated thermal nitrogen oxide (NO_x) generation kinetics, resulting in an 8% increase in NO_X emissions. 

Deep-sea heavy oil heating and viscosity reduction is key to improving recovery efficiency. Taking the heated oil flow in pipelines as the research object, a temperature field model of high-viscosity heavy oil in heating pipelines was established to analyze the influence of transmission distance, pipe diameter, heating temperature, and flow rate on the temperature rise of oil in the liquid/solid interface region (y/D < 0.1).Results demonstrate that an 80 °C pipe heating temperature yields the maximum interfacial temperature rise. Pipe diameter enlargement elevates interfacial oil temperature through increased heated surface area. A thermal inflection point emerges when the Reynolds number exceeds 2300 at pipe diameters of 151.66 mm, indicating aminar-to-turbulent flow transition that intensifies interfacial convective heat transfer. Under prescribed conditions, elevation of pipe heating temperature to 140 °C augments the effective heat transfer coefficient from 63.14 W/(m²·°C) to 134.24 W/(m²·°C), constituting a 52.96% increase that thereby enhances interfacial convective heat transfer effects.

The effect of nano-metakaolin on the tensile properties of fly ash cement mortar at early age was investigated. 4 nano-metakaolin contents (1%, 3%, 5%, 7%) and 3 fly ash contents (10%, 20%, 30%) were taken into consideration. 40 cement mortar specimens were prepared in the laboratory. The direct tensile experiments were executed on the prepared mortars at early age (3h, 4h, 5h, 6h, 8h, 10h). The digital image correlation technique was applied to monitor the strain on the surface of specimens during the tensile process. Tensile behavior of the mortar specimens were obtained. The results show that the addition of fly ash leads to a reduction in the tensile strength, the tensile strength of mortar with 30% fly ash at 6h decreased by 52.4% compared to ordinary mortar. The addition of nano-metakaolin significantly improves the tensile properties of both ordinary mortar and fly ash cement mortar at early age. Specifically, the tensile strength of mortar with 5% nano-metakaolin reached 4 times that of ordinary cement mortar at 6h. Moreover, incorporating 5% nano-metakaolin increased the 6h ultimate tensile strength of mortar containing 10% fly ash by 23%.  

To achieve accurate perception of the operational status and effective fault early warning of marine diesel engines, a multimodal digital twin method integrating mechanism simulation and sensor measurement information was proposed. This method introduced a performance degradation correction mechanism to construct a high-fidelity thermodynamic simulation model of diesel engines, designed a feature extraction network integrating multi-scale convolution and attention mechanisms, and accomplished deep feature extraction and cross-modal fusion of the two types of complementary information. Taking the deviation degree as the early warning index, the self-learning of performance parameter thresholds was realized combined with kernel density estimation, and a fault early warning mechanism with dynamic adaptability was constructed. The effectiveness and applicability of the proposed method under actual operating conditions were verified based on the operational data of the 9L34DF dual-fuel marine diesel engine.

To address the issues of hull damage, sinking, and personnel entrapment caused by ship collision accidents, a path planning method for ship engine room rescue robots based on an improved ant colony algorithm was proposed. Aiming at the problems of low search efficiency and slow convergence speed of traditional ant colony algorithm in path planning, the heuristic function and pheromone update were improved. Firstly, an adaptive iterative weighting factor coupled with a local obstacle density correction term was introduced to mitigate the low search efficiency prevalent in the algorithm’s initial stages. Secondly, pheromone reinforcement was strategically applied to the optimal path, while appropriate pheromone diminution was executed on suboptimal paths following each iteration, thereby suppressing the detrimental influence of inferior routes. Thirdly, adaptive parameters were introduced to enable the algorithm to assign different weights to the global optimal, iterative optimal, and worst paths at different iteration stages, thereby enhancing the convergence and robustness of the algorithm. Through the above improvements, the algorithm has achieved an optimization transformation from relying solely on distance and pheromone concentration to comprehensively considering target point gravity, obstacle rejection, local environment complexity, and adaptive search strategies. Experimental results show that the improved algorithm shortens the path by 10 % compared with the traditional algorithm, redundant turning nodes are reduced by 65%, and the number of iterations is reduced by 96.4%. The validation in real ship cabin scenarios further demonstrates that the proposed method significantly reduces detours and redundant turning points in path planning, accelerating convergence speed and effectively avoiding local optimum traps, thereby realizing more efficient and stable path search in complex environments.

To reduce the reliance of highly procedural and highrisk maritime search and rescue (SAR) tasks on traditional manual rescue modes and improve China’s maritime SAR response efficiency, this paper proposed a collaborative optimization method for rescue base cluster deployment and heterogeneous unmanned surface vehicle (USV) configuration considering efficiency balance. This method accounted for both the timeliness of maritime response and the distribution characteristics of risk levels, established a rescue efficiency evaluation model, and was applied to quantitatively analyze the comprehensive performance of base cluster deployment and USV configuration schemes. On this basis, with the objective of maximizing the overall rescue efficiency of the responsible sea area, a collaborative optimization model was established by comprehensively considering practical constraints such as investment budget limits, endurance capacity of USVs, and communication coverage radius. Furthermore, an exact solution algorithm based on linear transformation was designed to achieve efficient solving of the optimal configuration scheme under complex constraints. The algorithm verification results show that when the side length of the sea area unit exceeds 1.5 km, the algorithm can obtain an exact solution within ten minutes, and the calculation accuracy improves with grid refinement, which can more accurately reflect the characteristics of the actual marine environment. The case study further demonstrates that optimizing the collaborative scheme of rescue base cluster deployment and heterogeneous USV configuration can effectively alleviate the unbalanced spatial distribution of maritime rescue efficiency. The sensitivity analysis results indicate that as the objective function adjustment coefficient increases, the optimization results tend to prioritize response efficiency, and the deployed USV types gradually shift from mixed types to highperformance types. Correspondingly, the number of covered responsible sea area units decreases by 17.8%. To maintain the original area of the responsible sea area without reducing rescue efficiency, an additional annual investment budget of 21 000 to 97 000 RMB is required.

To address the task allocation problem of heterogeneous unmanned aerial vehicles (UAVs) in diverse mission scenarios, a task allocation algorithm for heterogeneous UAV swarms based on the improved slime mold algorithm (SMA) was proposed. Firstly, from the perspectives of task timeliness and performance parameters, and based on the existing multiparameter modeling framework, this paper further improved the parameter characterization of task diversity and UAV heterogeneity to better adapt to the multitype tasks and multiconstraint scenarios. Secondly, to address the problems of slow convergence speed and low solution accuracy of the SMA, optimization was carried out by introducing Tent chaotic mapping, linear dynamic search range, improved individual update mechanism and optimal neighborhood perturbation strategy. Finally, the improved SMA was integrated with the proposed task allocation model, and its effectiveness was verified by setting task scenarios with different scales. Simulation results show that the proposed algorithm can achieve reasonable task allocation with minimal task cost under different scenario scales. Compared with benchmark methods, the proposed algorithm reduces the comprehensive objective function by at least 10.6% and 15.4% in two different task scales, respectively.

To enhance the mechanical performance of concrete under dynamic loading and investigate the reinforcing effect of nanomaterials, a study was conducted on the dynamic uniaxial compressive performance of concrete mixed with 0.05% graphene. Uniaxial compressive performance tests and finite element simulations were conducted on graphene concrete and ordinary concrete by using five different strain rate levels (10^-5s^-1, 10^-4s^-1, 10^-3s^-1, 5×10^-3s^-1, and 10^-2s^-1), and the differences in dynamic mechanical properties and strain rate effects between the two types of concrete were compared and analyzed. The experimental results show that the compressive strength and elastic modulus of both types of concrete have significant strain rate sensitivity, and increase with the increase of strain rate. The performance improvement of graphene concrete varies with strain rate. Compared to ordinary concrete, the maximum increase in compressive strength, elastic modulus, peak strain, and energy absorption capacity of graphene concrete is 16.17%, 5.02%, 7.27%, and 20.20%, respectively. The finite element numerical simulation results are in good agreement with the experimental test results, verifying the effectiveness of the simulation method. This study can provide theoretical support and technical reference for the application of graphene nanomaterials in concrete engineering.

Under the background of port intelligence upgrades, the dynamic complexity of business scenarios and the multi-source heterogeneity of data have exposed gaps in the “perception-cognition-decision” chain of current port intelligence systems. Knowledge graphs excel at symbolic reasoning but struggle with handling multi-modal semantics and dynamic knowledge fusion. Large models possess powerful natural language capabilities but face challenges in achieving accurate and reliable decision-making reasoning due to insufficient interpretability and lack of domain knowledge. This situation of “separation of perception and cognition, and disconnection of generation and reasoning” makes it impossible for a single technology to meet the port’s demands for highly reliable, interpretable, and adaptive intelligent decision-making. Therefore, integrating multi-modal knowledge graphs and large models has become a key path for driving the evolution of port intelligence systems. This paper systematically reviewed the related work on artificial intelligence, knowledge graphs, and large models in port intelligence, analyzed the driving mechanism of their integration under the dual perspective of industrial demand and technology integration, and constructed hierarchical technical and functional frameworks. Meanwhile, based on port engineering practice and development status, this paper identified and discussed key technical challenges faced in achieving deep integration, aiming to provide theoretical basis and practical guidance for related research and engineering applications.

This paper addressed the vessel schedule recovery problem (VSRP) for container liners suffering delays caused by disruptive incidents, and introduced the shipping carbon trading mechanism. A dual-objective optimization model for VSRP was established to minimize voyage schedule recovery costs and maximize customer service level. For scenarios with anticipated operational disruptions, the optimal combined strategy consisting of speed adjustment, port skipping and port swapping was solved. An improved adaptive non-dominated sorting genetic algorithm II (NSGA-II) was designed to solve the proposed model. Multiple scenario-based numerical examples verify the effectiveness of the proposed model and improved algorithm in this paper. Numerical results show that different durations of anticipated disruptions correspond to distinct optimal combined strategies for schedule recovery. Under the dual-objective optimization without preference, utilizing information on anticipated disruptions can reduce voyage recovery costs by 18.31% on average. Sensitivity analysis shows that when the carbon trading price rises, both the schedule recovery cost and vessel carbon emissions decrease simultaneously if the preference weight of the carbon emission reduction objective is large. Besides, an increase in carbon quotas will directly cut down the schedule recovery cost. In contrast, when the preference weight of the carbon reduction objective is small, carbon emissions follow a trend of decreasing first and then increasing. The research conclusions can provide theoretical support and decision-making references for shipping enterprises to formulate schedule recovery schemes under operational disruptions.

Traditional cement-based piezoelectric composites (0-3 and 1-3 types) suffered from limited stress transfer efficiency and low piezoelectric output due to random piezoelectric phase distribution and fiber breakage. To address this issue, this paper developed a new cement-based piezoelectric composite based on the topological structure of triply periodic minimal surfaces (TPMS). Two typical TPMS configurations, Diamond and Karcher-Tuite, were parametrically modeled by using Python and the level-set method, and a piezoelectric-structure coupling finite element model was established by using Abaqus to evaluate the effects of piezoelectric phase volume fraction (10.0%~29.2%) on stress distribution and output performance (d₃₃, g₃₃, V). Results show that the continuous three-dimensional network of TPMS structures can effectively optimize the stress transfer path and avoid local stress concentration, thereby achieving excellent mechano-electrical conversion efficiency. When the volume fraction of the piezoelectric phase is 29.2%, the piezoelectric coefficient d₃₃ of Diamond and Karcher-Tuite composites reaches 148.5 pC/N and 103.7 pC/N, respectively, which is significantly superior to those of traditional 0-3 and 1-3 configurations. Through systematic numerical simulations, this paper reveals the intrinsic correlation between the topological characteristics of TPMS and the macroscopic piezoelectric properties, providing a theoretical basis for the configuration optimization and experimental design of self-powered sensing materials with high sensitivity and high durability.

To systematically investigate the effects of different interphase force models on numerical simulation results, transient numerical simulations of gas-liquid two-phase flow were carried out by using the Euler-Euler two-fluid model based on the open-source platform OpenFOAM. The prediction performances of various interphase force closures were analyzed, and the accuracy of each model was validated by comparison with experimental data and reference results. The study covered low, medium, and high Reynolds number conditions, corresponding to various gas-liquid flow regimes. It focused on revealing the mechanisms of drag, lift, wall lubrication, and turbulent dispersion forces governing bubble dynamics and radial void fraction distribution. The results show that there exists no universal model valid for the entire range of flow conditions, and the choice of interphase force models depends on the specific bubbly flow regime and Reynolds number range. At low Reynolds numbers, the drag force model dominates the bubble migration process. At high Reynolds numbers, the lift force model plays a dominant role in phase distribution patterns, shifting the void fraction peak from the wall region to the core flow region. The turbulent dispersion force tends to homogenize the radial void fraction distribution. Furthermore, the coupling effect among lift force, wall lubrication force and turbulent dispersion force significantly improves the prediction accuracy of radial phase distribution. The simulation results determine the optimal combinations of interphase force models within different Reynolds number ranges. Based on a systematic analysis of the mechanisms of each interphase force under various Reynolds numbers, this paper proposes a strategic framework for selecting interphase force models, which provides a theoretical basis and optimization guidance for the multiphase flow model configuration in numerical simulations of complex bubble flows. The study further confirms that, under low gas fraction conditions, the phase distribution of vertical adiabatic bubbly flow can be accurately predicted even if bubble coalescence and breakup effects are neglected, which provides a feasible reference for the simplification of multiphase flow models.

Ship pipeline path planning is susceptible to problems such as local optima and path redundancy. To solve these issues, this paper adopted the blocked-path pruning A* algorithm (BPA-star) to study pipeline layout optimization. After establishing the geometric model of the pipeline working space, the algorithm was improved by integrating pruning segmentation and blocked-path iteration techniques. This method not only avoids the local optimum trap of traditional search algorithms and expands the global search range, but also eliminates redundant routes and unnecessary turning points, thereby effectively improving the quality of pipeline planning. The results show that for single-pipeline cases, the BPA-star algorithm achieves optimal values in terms of path length, number of turns and energy cost. For multi-pipeline cases, it produces a more compact layout that fits the hull structure well. Compared with the conventional A* algorithm, the proposed method delivers better pipeline connection performance, along with superior economic efficiency and adaptability. Without the directional guidance of extension segments, the energy value of pipelines planned by the algorithm decreases by 45.68%, and the installation adaptation length increases by 400%. With the directional guidance of extension segments adopted, the number of pipeline turns decreases by 8.64%, and the installation adaptation length increases by 54.64%. The findings can provide guidance for ship pipeline layout design and have practical application value for improving pipeline design and construction efficiency.

Aiming at the robust control problem of control systems under unknown nonlinear dynamics, time-varying disturbances, input saturation and Gaussian noise, an adaptive sliding mode control method deeply integrating event-triggered mechanism and dynamic coupling strategy was proposed. Firstly, the dynamic surface control (DSC) technique combined with radial basis function neural network (RBFNN) was adopted to approximate the unknown dynamics of the system, and a staged error constraint strategy was designed to achieve dynamic collaborative optimization of convergence speed and steady-state accuracy. Secondly, a time-varying disturbance observer was introduced to estimate disturbances such as wave disturbances online, and an intelligent smoothing processing mechanism driven by Gaussian error function was used to handle the problem of asymmetric input saturation. Furthermore, by combining the event-triggered mechanism, the adaptive dynamic threshold control was used to reduce the control update frequency and decrease the consumption of computing resources. Based on the Lyapunov stability theory, it is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error can converge to a preset neighborhood. Simulation results show that the proposed method significantly improves the system’s anti-interference ability and control efficiency, providing theoretical support for the application of related control theories in engineering practice.

Spraying is a common method for fabricating superhydrophobic surfaces, yet it suffers from low bonding strength between coatings and substrates, poor durability and unstable air cushions in water. A composite fabrication strategy combining micro-arc oxidation (MAO) and two-step spraying was proposed for aluminum substrates. Firstly, porous structures were constructed on aluminum substrates via micro-arc oxidation. Secondly, fluorocarbon resin doped with hydrophobic SiO₂ nanoparticles and SiO₂ nanoparticle superhydrophobic solution were sprayed sequentially, and superhydrophobic surfaces were obtained after curing at room temperature, with a static water contact angle of 162.5° and a sliding angle of merely 1.8°. The comprehensive performances were systematically investigated through friction test, gravel impact test, self-cleaning test, electrochemical corrosion test, salt water immersion test and drag reduction test. The results show that the as prepared double layer SiO₂ superhydrophobic surface possesses excellent mechanical durability. Its corrosion current density is reduced by three orders of magnitude compared with the bare aluminum substrate. The drag reduction rate reaches 69.5% at a water flow velocity of 0.5 m/s in specimen scale tests, and achieves 54.8% at a sailing speed of 0.3 m/s in ship model tests. The porous structure formed by micro-arc oxidation enhances the interfacial bonding strength between coating and substrate. Moreover, the SiO₂ nanoparticles embedded in the resin can strengthen the coating and dynamically repair damaged micro/nanostructures, synergistically endowing the surface with stable superhydrophobicity. By rational coating structure design, the overall performances of superhydrophobic surfaces are effectively improved. This study provides experimental basis and theoretical support for the engineering application of superhydrophobic surfaces in marine fields.

To mitigate the deterioration of ship seakeeping performance induced by liquid tank sloshing and reduce the associated navigation safety risks, this paper employed the finite volume method to solve fluid control equations and utilized the VOF method to capture the free liquid surface. A numerical model was developed to investigate the sloshing suppression mechanism and flow field characteristics of vertical symmetric baffles. The study focused on the suppression effect of vertical symmetric baffles with different lengths under sway excitation, as well as their impacts on flow field characteristics such as the free surface of the liquid tank, tank wall pressure, and flow field velocity. The results show that for rectangular liquid tanks with an aspect ratio close to 1, the vertical installation of symmetric baffles at the free liquid surface can significantly suppress sloshing; the sloshing suppression effect varies significantly with different baffle lengths, and the optimal baffle length is set at 0.7 times the width of the liquid tank.

To improve the anti-friction and wear resistance performance of marine internal combustion engine bearing bushes under harsh operating conditions, this paper adopted the scraping and thermal curing process to prepare a polyimide/epoxy resin/tungsten disulfide (PI/EP/WS₂) composite coating on the surface of an aluminum alloy substrate, and explored the influence law of the bonding agent ratios on its mechanical and tribological properties. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) were used to analyze the morphology and element distribution of the coating surface, cross-section and wear scars, a microhardness tester was employed to measure the coating hardness, and a friction and wear tester was adopted to investigate the friction coefficient and wear rate of the coating under different loads and frequencies under dry friction conditions. Results show that with the increase of load and frequency, the wear rate and friction coefficient of the coating gradually increase, and the bonding agent ratios has a significant impact on the coating properties. When the bonding agent ratios is 2, the tungsten disulfide solid lubricant in the coating is uniformly dispersed in the polymer, the coating structure is dense, and the microhardness is the highest, reaching 56.7 HV. Under dry friction conditions at a reciprocating frequency of 3 Hz and a load of 5 N, the coating with bonding agent ratios of 2 exhibites the best overall tribological performance, with an average friction coefficient of 0.06 and a wear rate of 1.50×10^-4 mm³/(N·m). The superior performance can be attributed to the following factors: in terms of friction reduction, the layered WS₂ with weak interlayer van der Waals forces facilitates easy shearing, endowing the coating with excellent anti-friction properties. Regarding wear resistance, when the polymer content is too high, the insufficient hardness of the polymer matrix leads to plastic deformation and adhesive wear; conversely, when the polymer content is too low, the bonding strength between the coating and the substrate is inadequate, resulting in coating spallation. This study can provide experimental evidence and data support for developing high-performance protective coatings for marine engine bearing bushes.

Visual observation technology and nonlinear fitting method were adopted to analyze the fluid behavior characteristics in the cavity of the rotating disk reactor. Water, glycerol and sodium dodecyl benzene sulfonate solution were selected as working fluids. A high-speed camera and Image J image processing software were used to investigate the flow patterns and breakup modes of fluid in the cavity. The critical condition equation for flow pattern transition was fitted, and the influence laws of operating parameters on the characteristic droplet diameter and droplet distribution uniformity index were explored. Results show that the typical flow patterns include ligament flow, ligament-droplet flow, and droplet flow. Meanwhile, the breakup mechanisms consist of film-to-droplet and film-to-ligament-to-droplet transitions. The cumulative droplet volume follow the Rosin-Rammler (R-R) distribution, with characteristic droplet diameters ranging from 1 to 4 mm, and the droplet distribution uniformity index between 2 and 8. Rotor speed and fluid viscosity significantly influence on the fluid behavior characteristics in the cavity zone. The findings contribute to a deeper understanding of the internal fluid behavior characteristics of supergravity devices and can provide basic data and theoretical references for constructing mass transfer models.

Pirate attacks pose a serious threat to maritime shipping security. An accurate risk assessment model is critical for route planning and emergency decision-making. To scientifically assess piracy risks, a pirate attack risk assessment model based on an improved Bayesian network was proposed in this study. The Fisher optimal segmentation algorithm was introduced to enhance the model’s node-state settings, classification accuracy and scientific validity. Based on the screened samples and node-state settings, the expectation-maximization (EM) algorithm was used for Bayesian network parameter learning. Meanwhile, an improved tree structure learning algorithm was adopted to reduce the complexity of model structure learning. The proposed model improves prediction accuracy by 5.44% compared with the traditional Bayesian networks while reducing structure learning complexity by 21.43%. In addition, compared with random forest and backpropagation (BP) neural network models, it achieves improvements of 1.23% and 2.83% in prediction accuracy, respectively. This study provides robust decision support for the scientific prediction of piracy risks.

To reveal the influence mechanism of jet oscillation on the removal of residual palm oil during the dynamic cleaning of shipboard cargo tanks, dynamic cleaning experiments were carried out on a self-built test platform. A numerical simulation model for jet oscillation tank cleaning was established by using FLUENT, combined with dynamic mesh and user-defined functions. The effects of jet oscillation velocity on the cleaning performance of palm oil were systematically analyzed. The results show that the cleaning mechanism of palm oil is the coupling effect of wall pressure and shear stress. During the cleaning process, wall pressure acts first as the dominant factor, breaking through the palm oil layer attached to the tank wall and forming an initial oil-free zone. Afterwards, the shear stress generated by the radial expansion of the jet thoroughly strips the residual oil from the wall surface. The horizontal oscillation velocity of the jet is a key parameter affecting cleaning performance, and it has a significant negative correlation with tank wall pressure and maximum shear stress. Excessively high horizontal oscillation velocity leads to jet motion lag, which reduces the effective coverage area of the jet “water pad” and lowers the utilization efficiency of shear stress, thus degrading the cleaning performance. Under the test conditions, the optimal matching between wall pressure and shear stress is achieved at a horizontal oscillation velocity of 1.11 r/min, the effective coverage area of the “water pad” is relatively large, the utilization efficiency of shear stress reaches the maximum, and the oil removal performance is the best. The vertical oscillation velocity is also a key factor affecting the cleaning effect, and it needs to be reasonably matched with the horizontal oscillation velocity. With the vertical oscillation velocity keeps constant, an excessively high horizontal oscillation velocity results in insufficient deep cleaning of the tank wall, while an excessively low value enlarges the blind area. Increasing the vertical oscillation velocity will further widen the spacing between jet cleaning paths, expand the blind area and degrade the cleaning quality. Comparative analysis shows that the combination of 1.11 r/min (horizontal) and 20 mm/s (vertical) oscillation velocity achieves the best performance. Under this combination, the synergistic effect of wall pressure and shear stress is the strongest, and the effective coverage area of the “water pad” is relatively large, which can fully cover and peel off the residual palm oil on the wall. While achieving a 100% cleaning effect, the time consumed is only 18.75 s. Compared with the worst parameter combination that also achieves a 100% cleaning effect, the cleaning efficiency of this optimal working condition is improved by 50%, which can be used as a reference for efficient tank washing operations of actual ships.

The “breakwater + wind turbine” integrated utilization model has gradually become a focal point in offshore wind energy research. To explore the dynamic response characteristics of the breakwater-wind turbine system under the combined action of wind and seismic loads, this paper developed a three-dimensional coupled numerical model of the integrated breakwater-wind turbine structure by using PLAXIS. The horizontal displacements at the top of the tower and breakwater were used as the primary indicators to conduct a comparative analysis of the system’s dynamic response under various site and loading conditions. The results show that due to the difference in stiffness between the tower and the breakwater, the displacement at the top of the tower is significantly larger than that at the breakwater. Compared with the effects of wind load or seismic load alone, the combined wind-seismic loading significantly amplifies the system’s displacement peak, and this amplification is not simply a linear superposition. Furthermore, the wind-seismic interaction alters the sensitivity of the dynamic response of the breakwater-wind turbine system to the properties of the site soil. Therefore, in practical engineering design, the combined effect of different loads must be considered comprehensively. The conclusions of this paper can provide valuable references and guidance for the dynamic response analysis and design of “breakwater + wind turbine” integrated projects.